Application of Structural Equation Modeling to the Social Sciences: A Brief Guide for Researchers

Abstract

Emanating from a family of statistical techniques used for the analysis of multivariate data to measure latent variables and their interrelationships, structural equation modeling (SEM) is briefly introduced. The basic tenets of SEM, the principles of model creation, identification, estimation and evaluation are outlined and a four-step procedure for applying SEM to test an evidence-based model of eating disorders (transdiagnostic cognitive-behavioural theory; Fairburn, Cooper, & Shafran, 2003) using previously obtained data on eating psychopathology within an athletic population (Shanmugam, Jowett, & Meyer, 2011) is presented and summarized. Central issues and processes underpinning SEM are discussed and it is concluded that SEM offers promise for testing complex, integrated theoretical models and advances of research within the social sciences, with the caveat that it should be restricted to situations wherein there is a pre-existing substantial base of empirical evidence and a strong conceptual understanding of the theory undergirding the research question.